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  Table of Contents    
Year : 2011  |  Volume : 13  |  Issue : 55  |  Page : 371-377
Risk of hypertension related to road traffic noise among reproductive-age women

Department of Environmental Sciences, Vytautas Magnus University, Donelaicio St. 58, 44248-LT, Kaunas, Lithuania

Click here for correspondence address and email
Date of Web Publication28-Nov-2011

Chronic noise exposure is associated with adverse pathophysiological effects, which may contribute to the progression of hypertension. However, evidence supporting its effect on women is still inconsistent. The aim of the study was to examine the hypertension risk related to road traffic noise in residential settings in an urban community amongst reproductive-aged women. Cross-sectional study data including 3,121 pregnant women, 20-45 years old, and a geographic information system (GIS) to assess the average road noise (LAeq 24 hr) for every subject at the current residential address were used. Effects on physician-diagnosed hypertension were estimated by logistic regression with adjustments for age, social status, marital status, education, alcohol consumption, ethnic group, parity, body mass index, chronic disease, and exposure duration. The prevalence of hypertension amongst women aged 20-45 years in the lowest exposure category was 13.1% in comparison to 13.6% and 18.1% amongst those exposed to the medium and the highest exposure category, respectively. After making adjustments for the selected variables, no exposure effects [Odds ratio (OR) ≈ 1.0] were noted in the medium exposure category [51-60 dB(A)]. However, a slight increase was noted in the highest exposure category [≥61 dB(A)), OR 1.36; 95% CI 0.86-2.15]. The effect was more pronounced amongst women aged 30-45 years and a positive exposure-response relation was indicated for hypertension: An effect was seen at noise levels 51-60 dB(A) (OR = 1.03; 95% CI 0.72-1.49) and at >61 dB(A) (OR = 1.94, 95% CI 1.01-3.72). The present study shows some evidence for an association between the residential road traffic noise and hypertension amongst reproductive-aged women, and an exposure-response relationship.

Keywords: Age group, exposure-response relationship, hypertension, pregnant women, road traffic noise

How to cite this article:
Bendokiene I, Grazuleviciene R, Dedele A. Risk of hypertension related to road traffic noise among reproductive-age women. Noise Health 2011;13:371-7

How to cite this URL:
Bendokiene I, Grazuleviciene R, Dedele A. Risk of hypertension related to road traffic noise among reproductive-age women. Noise Health [serial online] 2011 [cited 2023 Mar 26];13:371-7. Available from: https://www.noiseandhealth.org/text.asp?2011/13/55/371/90288

  Introduction Top

Chronic noise exposure is associated with progression of cardiovascular diseases. [1],[2] Some authors findings show that community noise may also have adverse effects on reproductive outcomes. [3] Noise is one of the major environmental hazards of the modern world, originating from a wide variety of sources, including traffic (air, road, or rail) or industrial facilities. [4] Road traffic is the most important source of community noise. [5] Approximately, 30% of the European Union population is exposed to road traffic noise with an equivalent sound pressure level (L eq ) exceeding 55 dB(A) at daytime, [6] while 20% are exposed to noise levels above 65 dBA. [4] Noise exposure is associated with a number of health effects. It can reduce the sleep quality as well as cause physiological, mental, and social effects. [7] Noise-related stress persisting over long periods can lead to exhaustion of compensatory mechanisms and a decrease in the body's regulatory capacity. Therefore, in many cases adverse health effects are to be expected after a long duration of exposure, in general. [8]

Long-time exposure to noise could result in an increase in hypertension, cardiovascular risk as well as permanent cardiovascular changes, such as atherosclerosis. [9],[10],[11] A Swedish study showed that 55 dB(A) (LAeq 24 hr) noise level increased the hypertension risk by 60% for people exposed to aircraft noise, and 72 dB(A) noise level by 80%. The association with aircraft noise was stronger in men compared to women. [12] Studies performed in the last couple of years showed positive associations between road traffic noise and hypertension. [13],[14],[15],[16],[17],[18] The association with hypertension is relatively well established for occupational noise exposure, which has been confirmed in a recent meta-analysis [2],[13],[19] and original papers. [20] However, recent studies on road traffic noise and hypertension are heterogeneous with respect to effect size. [14],[15],[16],[17],[18],[21] It was observed that the effects differed amongst males and females, [15],[16] and across age groups. [17] The epidemiological studies on hypertension risk relied on different methods of assessing exposure, measurement of health effects and control of confounding variables. This presented difficulties in making comparisons between investigations and generalizing results.

The present study reports the prevalence of physician-diagnosed hypertension in an epidemiological study of pregnant women with a detailed assessment of traffic-generated noise levels at the subjects' current residential addresses using a geographical information system (GIS). Further, the study also included individual questionnaire information on major risk factors for hypertension, such as the occupational noise exposure. Through improvements in individual noise exposure assessment and controlling for various confounding variables, the present study aims to offer the hypertension risk estimation to examine the dose-response relationship for the susceptible population group.

  Methods Top

Information about study participants

An epidemiological study of pregnant women was conducted in Kaunas city, Lithuania, as a part of the European Commission FP6 HiWATE project. [22] To recruit women who were in the early stages of pregnancy, the prenatal care practices were asked to inform their newly enrolled patients about the study. Next, the blood pressure of the patients was measured. On their first visit to a general practitioner, all pregnant women living in Kaunas city between 2007 and 2009 were invited to join the study. These women were enrolled at 23-35 weeks of gestation (97% till 25 weeks) at the four prenatal care clinics affiliated to the hospitals of the Kaunas University of Medicine. Participation was on a voluntary basis and the women were enrolled in the study only if they consented to participate in the cohort. The study ethics complied with the Declaration of Helsinki. The research protocol was approved by the Lithuanian Bioethics Committee. Further, verbal informed consent was also obtained from all subjects. In total 5202 women were approached; 79% of them agreed to participate in the study. Women with multiple pregnancies (150) or having inconsistent data for estimating noise exposure (mostly students moved out of the city during pregnancy, 839) were excluded. The study population included 3,121 women, in the age group of 20-45 years at the time of interview, with a minimum length of one year of current residence.

Assessment of hypertension and confounders

The study subject was defined hypertensive if two or more of the physician's blood pressure measurements were: A systolic blood pressure ≥140 mmHg or a diastolic blood pressure ≥90 mmHg, regardless of antihypertensive medication or controlling of blood pressure.

Pregnant women were asked to complete questionnaires provided at the clinic. The interview queried women regarding demographics, job characteristics, self-reported occupational noise exposure, chronic diseases (cardiovascular, respiratory, renal, and diabetes), and residence duration. We also asked women to report their age at inclusion (less than 30 years, 30 years and more), educational level (primary, secondary, university), social status (worker, student, unemployed-low; housekeeper, officer - medium; manager, company owner - high), marital status (married not married), smoking during pregnancy (non-smoker, smoker <5 cigarette per day, and smoker ≥5 cigarette per day), alcohol consumption (0 drinks per week, mostly one drink per week, 2 and more drinks per week), blood pressure (<140/80 mm/Hg, ≥140 or ≥ 90 mm/Hg), body mass index (BMI) (<25, 25-30, >30), and other potential risk factors for hypertension. To assess the potential confounding variables we used Chi square test. Predictor variables whose univariate test showed a P value of <0.25 in relation to the outcome were included in the regression models.

Assessment of noise exposure

No measurements of noise levels were conducted. Instead, we used a GIS and strategic noise map to assess the outdoor noise exposure from traffic. The Kaunas municipality local noise measurement data base and strategic noise map from years 2007-2008 were used to estimate the noise exposure for the residential locations of the participants. The road traffic noise exposure of the subjects was calculated at the most exposed facade of the dwelling applying the Finnish and Swiss methodology. The methodology was based on an EMPA StL-86 model, using an acoustic algorithm. [23] Strategic Kaunas noise map were created in accordance with requirements of the European Environmental Noise Directive (END) [24] and European Commission Working Group Assessment of Exposure to Noise (WG-AEN). [25] For the analyses, we used EU standard noise metric LAeq 24 hr.

To evaluate LAeq 24 hr noise level, we used these input data: Road network, traffic flow, road surface type, road surface construction, road gradient, speed fluctuations at road, building heights, land-use data, industrial source data, barriers (building, wall, obstacle outlines), meteorological data, population data.

Traffic flow data were prepared for noise modeling on the basis of GIS database of strategic noise map of Kaunas municipality. The measurement of traffic flow intensity and noise level in the Kaunas city were carried out close to the main streets (282 measurement points), where traffic flow was more than 1200 vehicles/24 h. Using the cluster analysis methods we attributed the same noise level to the streets, where traffic flow intensity fluctuated less than 20 percent and the number of street lanes was the same. For road segments without traffic data, noise level mean values were calculated by using GIS. The data were recalculated into a factual level of noise. The noise was calculated at all points and a level of noise is attached to each residence in the area. For a limited area calculation points were placed in a grid, typically with a cell size of 10 × 10 m.

To attribute the noise exposure to every subject, the health data base and the environmental noise data base were joined. Every subject's full street address and residential noise level measurement data, and the current residence history data were combined to assess the individual noise exposure. A GIS assigning noise level was used for every woman by applying different GIS functions and possibilities. First, the study subjects data were converted to a database file structure for use in GIS software (ArcInfo version 9.3, ESRI). Geocoding was performed to obtain latitude and longitude coordinates for each patient's home address. Initially, 63% records were matched and 37% were left unmatched. All unmatched records were reviewed and corrected, leading to another 37% matched addresses (total of 3212). Then, a spatial join was perform that allows the GIS user to append the attributes of one data layer (patient address points) to the attributes of another layer (noise level) assessed with MapNoise for ArcGIS.

The non-weighted average road noise level at the geocoded current residential addresses of the participants was assessed.

Statistical analysis

Logistic regression was used to assess the relation between the average road noise exposure during 24 hours (LAeq 24 hr) as the categorical variable and the physician-diagnosed hypertension as the outcome variable. Noise measurements data were sorted in an ascending order. The average outdoor A-weighted sound pressure level (LAeq 24 hr) from the day-evening-night time was calculated and classified into three dB(A)-categories: Low, ≤50 dB(A); moderate, 51-60 dB(A); and high, ≥61 dB(A). We compared the risk of hypertension for three exposure categories using the reference category the subject group with an average road noise exposure below 50 dB(A). We used OR as a measure of association, and we applied logistic regression analysis to estimate the crude and adjusted ORs, and the 95% CIs for hypertension across three exposure categories. Three different types of logistic regression models were analyzed. The first model was unadjusted, the second partly adjusted model included age and BMI as covariates, while the third fully adjusted model included maternal age, BMI, social status, education, marital status, alcohol consumption, ethnic group, parity, chronicle disease, and exposure duration at the current address. We run the stratified analyses regarding the noise exposure duration (<10 years, ≥10 years) of different age groups (total sample 20-45, <30, ≥30 years), and self-reported occupational noise exposure (present, absent). We estimated the exposure effect by a multivariable analysis controlling for influence of major covariates included in the model that changed the adjusted ORs for noise by 10% or more. Two-tailed statistical significance was evaluated by using a P value of <0.05. Statistical analyses were carried out using the SPSS software for Windows version 12.0.1.

  Results Top

The mean and the standard deviation of the individual 24-hour noise exposure level (dB(A) LAeq 24 hr) in Kaunas during the study period were 49.5 and 6.23, respectively (range of 26-67 dB(A) LAeq 24 hr). A total of 423 hypertension cases amongst 3,121 pregnant women aged 20-45 years (13.6%) were registered. In general, it was observed that women who had an increased BMI, were 30 years or older, or had a low social status more often suffered from hypertension in comparison to women without such variables. The analysis by three different levels of road traffic noise exposure (low, moderate, and high) shows that prevalence of most characteristics of the exposure groups were similar [Table 1]. There were no differences in social and demographic characteristics, education, and occupational noise exposure. However, prevalence of BMI differed between exposure groups (P<0.05). The prevalence of hypertension amongst the 20-45 years age group women of the lowest exposure category [≤50 dB(A)] was 13.1%, of the moderate exposure category (51-60 dB(A)) was 13.6%, and of the highest exposure category [≥61 dB(A)] was 18.1%.
Table 1: Distribution of subjects for various characteristic by noise level

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Hypertension prevalence during the first trimester pregnancy amongst 20-45 years old women was coincident with the samples of the not pregnant 20-45 years old women in Lithuania. [25]

A modest exposure effects were noted for the three exposure levels (≤50, 51-60 and ≥61 dB(A)) demonstrating slight increasing hypertension odds ratios at increasing road noise levels amongst the 20-45 years age women [Table 2]. However, only 5.0% of all the study subjects lived in an environment where the average noise level (LAeq 24 hr) was higher than 61 dB(A). In this environment, 6.6% of all hypertension cases were registered. Therefore, the results were not statistically significant. The crude hypertension odds ratios of women exposed to moderate noise level was 1.04 (95% CI 0.84-1.29), while the OR of the highest exposure was 1.44 (95% CI 0.93-2.23) in comparison to the lowest exposure [≤50 dB(A)].
Table 2: Odds ratios and their 95% confidence intervals of hypertension associated with three levels of road traffic noise exposure and exposure duration using three models of adjusting

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The data showed that the unadjusted analyses were likely to be confounded by BMI and possibly also by other variables. Therefore, in the study concerning the noise effect on the different age groups, three models of adjusting were used: Unadjusted (crude results); partially adjusted, and fully adjusted. The increasing road noise exposure effects on hypertension were seen in the second and the third traffic noise exposure categories in all the models. However, a consistent statistically significant effect was only found in women ≥30 years in the third noise category [≥61 dB(A)]; OR = 1.88 (1.02-3.47) in the unadjusted model, OR = 1.90 (1.00-3.58) in the partially adjusted model, and OR = 1.94 (1.01-3.72) in the fully adjusted model. The data showed that an exposure effect of road traffic noise was stronger in the ≥30 years age group.

A modest exposure effect of the road traffic noise was indicated for 20-45 years old women who lived at exposure levels ≥61 dB(A). Here, after full adjustment the odds ratio was 1.36 (95% CI 0.86-2.15) in comparison to the lowest category [≤50 dB(A)].

No obvious effect was found between the women <30 years, whereas in the 30 years age group an exposure-response relationship was indicated. After full adjustment for potential confounding factors, we observed a statistically significant increased hypertension risk with exposure to moderate and high noise levels; adjusted OR 1.03, 95% CI 0.72-1.49 in 51-60 dB(A) and OR 1.94, 95% CI 1.01-3.72 in highest exposure category [≥64 dB(A)].

Seeking to study whether subjects that were exposed for longer times have a higher hypertension risk, we ran stratified analysis by residence duration. There was no evident difference between road traffic noise exposure below 10 years and above 10 years and effect on hypertension in the studied age groups. After full adjustment for potential confounding factors, we observed a slightly increasing risk with <10 years exposure for 20-45 years old women (OR 1.03, 95% CI 0.78-1.36 and OR 1.47, 95% CI 0.83-2.59), respectively, for 51-60 and ≥64 dB(A). However, there was no evident difference between road traffic noise exposure below 10 years and above 10 years and effect on hypertension in the studied age groups. The effect estimate for the exposure ≥10 years was also statistically non-significant (OR 0.95, 95% CI 0.69-1.75 and OR 1.34, 95% CI 0.61-2.91, respectively, for 51-60 and ≥64 dB(A). Similar results were found for ≥30 years age women, the corresponding OR was 0.93, 95% CI 0.51-1.70 and OR 2.18, 95% CI 0.74-6.38. Effect modification was not indicated for years in residence (P for interaction = 0.54).

[Table 3] shows how occupational noise could influence the hypertension risk to 20-45 years old women who lived in three different noise level categories.
Table 3: Crude and adjusted OR and 95% CI of hypertension associated with different levels of road traffic noise exposure to women exposed to occupational noise

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The results showed a positive relation between the road traffic noise, noise at the work place, and an increased risk of hypertension amongst the 20-45 years old women. The association was noted when important potential confounders were included in the model. The fully adjusted OR for women residing in the highest road noise category [≥61 dB(A)] not exposed to noise at work was 1.34 (95% CI 0.83-2.20), while OR for women exposed to noise at work was 1.52 (95% CI 0.35-6.55). Subsequently, we tested for the interaction effect of occupational noise exposure, road traffic noise exposure with hypertension by adding all the product terms in the regression models, while adjusting for potential confounders. However, the effect modification was not indicated (OR 1.25, 95% CI 0.29-5.30).

  Discussion Top

Through improvements in the individual noise exposure assessment and controlling for various confounding variables, the present study offers hypertension risk assessment based on the examination the exposure-response relationships for a susceptible population group. After simultaneously considering the known and the potential risk factors identified using personal data of the women sample, some evidence regarding the effect of traffic noise exposure amongst reproductive aged women on hypertension was observed. A statistically significant increased risk of hypertension (OR 1.94, 95% CI 1.01-3.72) to women of 30-45 years of age exposed to average noise level (LAeq 24 hr) of ≥61 dB(A) was observed. The evaluation of noise exposure included individual 24-hour noise measurements from road traffic by using high-resolution GIS techniques and methods separating road traffic noise from other noise sources, and self-reported occupational noise.

As a potential environmental hazard for a subset of women who are pregnant, environmental noise exposure has received increasing attention in the last decade. The epidemiologic evidence for association between exposure to road traffic noise and hypertension has been examined in a few studies. [14],[ 15],[17] The obtained results coincide with the recently published data on the influence of road traffic on hypertension risk in women. As shown by Barregard et al. [15] in a population-based study, when factors, such as road traffic noise, age, sex, heredity and BMI were included in the logistic regression models, and latency of >10 years was allowed, the OR for hypertension was 1.9 (95% CI 1.1-3.5) in the highest noise category (56-70 dB(A)). Another Lithuanian population-based cross-sectional study presented the effect amongst 40-59 aged subjects at noise levels 60-64 dB(A), OR = 1.27, 95% CI 1.02-1.58, and at > 64 dB(A), OR = 1.91, 95% CI 1.19-1.06. [26] The age of women has a significant influence on the hypertension prevalence. The present study showed that excess hypertension risk was found amongst women aged 30 years or more.

Noise is a stressor that affects the autonomic nervous system and the endocrine system. [27] An indirect effect of noise implies that neural responses induced by noise may elicit a spectrum of somatic activity, such as an increased secretion of catecholamine, and increased blood pressure. [3]

The noise exposure level experienced by the present study subjects, ranging from 26 to 67 dB(A) (LAeq 24 hr), represents the similar noise exposure experienced by subject of other studies. [15],[28] However, physiologic and psychological responses to noise may differ amongst populations and individuals. This could decrease the comparability amongst results of different studies.

The present study's population was homogeneous with respect to the ethnic culture and the health care system. The other strengths of the present study include the use of personal data on possible risk factors for hypertension. This enabled us to control of the potential confounding factors and the covariates of hypertension. Therefore, the study provides valid information for evaluating the association between noise exposure and hypertension. The hypertension prevalence based on self-reports are most likely, substantially underestimated. A recent study concluded that as many as two-thirds of hypertension cases were missed using self-reporting, [29] although other studies have shown sensitivity of 71%. [30]

Incorrect classification of hypertension cases as non-cases and vice versa was not likely, as physician-diagnosed hypertension is generally considered reliable. The estimation of hypertension during the pregnancy period was of course less reliable. Thus, some incorrect classification of hypertension cases may have occurred. However, the assignment of cases was independent of exposure assessment. Therefore, such classification errors were probably non-differential and may have tended to underestimate the traffic noise effects.

The most important source of error and possible bias in the present study (as was the case in most studies in which exposure was based on the place of residence) was the possible incorrect classification of exposure, because of estimated noise levels refer to the most exposed front of the houses. Inaccurate exposure estimates may lead to loss of power and precision, and attenuation in health risk estimates, depending on the type of error model. [31] The extent to which this happens depends on the relationship between the exposure index that is used and the "true" exposure. The epidemiologic study was conducted using a categorized (low, medium, and high) 24 hour average noise level as the exposure index. When the exposure index was categorized, exposure misclassification could bias the relative risk estimates either upwards or downwards (assuming an association truly exists). True personal exposure depends upon a number of exposure pathways; for example, time spent indoors versus time spent outdoors, time spent at specific locations, such as at work or home, and migration into or out of a study area. Nevertheless, factors expected to contribute to differences between area wide and individual exposures were most likely independent of exposure assessment, with a resulting underestimation of the effects of noise. However, one limitation of the noise effect measurement in the present study is that the noise exposure represented a summary noise index experienced by pregnant women without considering levels of individual noise annoyance. Moreover, the possibility that hypertension can be induced by environmental factors not studied or factors other than noise traffic-related pollutants cannot be excluded.

Previously publicized data indicate that identification of the group of susceptible subjects should be based on both environmental exposure and gene polymorphism. [32] The hypothesis that genetic variation at the angiotensinogen locus and G protein polymorphisms impacts on the individual susceptibility to develop essential hypertension has motivated a substantial body of research. [33],[34],[35] The current studies concluded that genetic polymorphisms increase the susceptibility to hypertonic disease in the context of environmental exposures through a variety of physiological mechanisms. Therefore, future studies must consider the contribution of both external factors (e.g., the intensity and duration of noise, chemical exposures, air pollution) and internal factors (e.g., individual noise annoyance, genetic susceptibility) of the study subjects.

The present study showed some evidence for association between the residential road traffic noise and hypertension amongst reproductive aged women, and an exposure-response relationship. Future studies should use larger samples, evaluation of blood pressure changes over pregnancy, individual noise annoyance, and genetic susceptibility-specific effect modifiers to account for differences in the exposure-response relationship.

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Correspondence Address:
Inga Bendokiene
Department of Environmental Sciences, Vytautas Magnus University, Donelaicio St. 58, 44248-LT, Kaunas
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1463-1741.90288

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Simone Leao,Kok-Leong Ong,Adam Krezel
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Argalášova-Sobotova, L. and Lekaviciute, J. and Jeram, S. and Ševcíková, L. and Jurkovicová, J.
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